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  2. Stop word - Wikipedia

    en.wikipedia.org/wiki/Stop_word

    In SEO terminology, stop words are the most common words that many search engines used to avoid for the purposes of saving space and time in processing of large data during crawling or indexing. For some search engines , these are some of the most common, short function words , such as the , is , at , which , and on .

  3. Natural Language Toolkit - Wikipedia

    en.wikipedia.org/wiki/Natural_Language_Toolkit

    Parse tree generated with NLTK. The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning ...

  4. spaCy - Wikipedia

    en.wikipedia.org/wiki/SpaCy

    spaCy (/ s p eɪ ˈ s iː / spay-SEE) is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython. [3] [4] The library is published under the MIT license and its main developers are Matthew Honnibal and Ines Montani, the founders of the software company Explosion.

  5. Comparison of programming languages (syntax) - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_programming...

    Python. The use of the triple-quotes to comment-out lines of source, does not actually form a comment. [19] The enclosed text becomes a string literal, which Python usually ignores (except when it is the first statement in the body of a module, class or function; see docstring). Elixir

  6. Python syntax and semantics - Wikipedia

    en.wikipedia.org/wiki/Python_syntax_and_semantics

    Numeric literals in Python are of the normal sort, e.g. 0, -1, 3.4, 3.5e-8. Python has arbitrary-length integers and automatically increases their storage size as necessary. Prior to Python 3, there were two kinds of integral numbers: traditional fixed size integers and "long" integers of arbitrary size.

  7. Text normalization - Wikipedia

    en.wikipedia.org/wiki/Text_normalization

    Text normalization is the process of transforming text into a single canonical form that it might not have had before. Normalizing text before storing or processing it allows for separation of concerns, since input is guaranteed to be consistent before operations are performed on it.

  8. Word divider - Wikipedia

    en.wikipedia.org/wiki/Word_divider

    In punctuation, a word divider is a form of glyph which separates written words.In languages which use the Latin, Cyrillic, and Arabic alphabets, as well as other scripts of Europe and West Asia, the word divider is a blank space, or whitespace.

  9. Stemming - Wikipedia

    en.wikipedia.org/wiki/Stemming

    NLTK – Software suite for natural language processing — implements several stemming algorithms in Python Root (linguistics) – Core of a word that is irreducible into more meaningful elements Snowball (programming language) – String processing programming language — designed for creating stemming algorithms